In lieu with our flagship event of the year, AIMed had encouraged anyone who has innovative ideas of how artificial intelligence (AI) will transform the future of medicine and healthcare, to participate in our annual Abstract Competition. Participating ideas can be a completed piece of work, an idea in progress or an initial project plan which an individual (or a group of like-minded) will like to showcase.

In order to enter, the abstract has to fall into either of the six categories: 1. Decision support and hospital monitoring; 2. Medical imaging and biomedical diagnostics; 3. Precision medicine and drug discovery; 4. Cloud computing and data security; 5. Digital medicine and wearable technology, and 6. Robotic technology and virtual reality.

AIMed is honored to have Dr. Robert Hoyt, Associate Clinical Professor, Internal Medicine Department, Virginia Commonwealth University; Dr. Todd Ponsky, Professor of Surgery, Director of Clinical Growth and Transformation at Cincinnati Children’s Hospital, and Dr. Orest Boyko, Associate Professor of Radiology, University of Southern California as judges to select the best abstracts prior to AIMed 19.

Starting from this week, AIMed will showcase the winner from each of the category, as they share with us their respective propositions, inspirations, and the kind of impact they will like to create.

Name of the winner: Richard Chen

Winning Category: Precision Medicine & Drug Discovery

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AIMed: For the benefit of readers who do not know you, could you please tell us more about yourself and your abstract idea?

Richard Chen: I am a high school senior from San Diego, California and I currently work at the University of California, San Diego’s Mentor Assistance Program, with my professor Igor Tsigelny and two research partners David Huang and Alvin You, in search for new, more effective compounds for the treatment of diabetic cataracts.

Past studies had shown that diabetic cataract is catalyzed by an enzyme called “Aldose Reductase” and its inhibitors can prevent or treat the condition. As such, my team and I used a machine/deep learning neural network to analyze the attributes of known inhibitor compounds to predict for new compounds that we could then test through simulations if they are, indeed, more effective.

AIMed: What inspired you to formulate the idea?

Chen: My professor had put me in charge of this idea when I was accepted into the Mentor Assistance Program. This is my first research project and I have no prior experience. Nevertheless, I have always wanted to be involved in the medical field. As I was uncovering my interests, I also realized I am into computer science. At a glance, when you think of computers, codes, and medicine, you don’t really see an intersection but AI in medicine has allowed me to combine these two very different fields into one project and I think that’s really motivating.

AIMed: What prompted you to take part in the Abstract Competition?

Chen: I was introduced to AIMed by my professor. He said I should read about it online and check out the Abstract Competition to see if I will like to participate. After learning what all this is about, I was like, sure, why not. It will be a cool experience for me and, to be honest, I don’t regret doing it.

It was a little overwhelming at first because everyone at the conference was professionals, clinicians or those who are already working in the field, not high school students like myself. But even then, I think they were very welcoming and open; they would talk to me and made me feel less intimidated.

AIMed: How did you find the whole process? What did you learn?

Chen: I think it’s important to get to know the people around me as they are the ones who keep me going. I don’t think I would be able to continue with this project if I didn’t receive the support from my professor and my research partners because there were times when it’s just difficult to complete certain things on my own.

I think it’s also important to talk to people. The more you talk to people, the more you will find opportunities. During the conference, my research partners and I spoke to tons of people and we learnt so much more than just standing there and didn’t say anything. Overall, I was definitely impressed. I never thought AI and computer science would play such a huge part in medicine and the competition made me realized differently.

I think what stood out to me most was what Dr. Chang had mentioned. Despite the coding and technical language, AIMed is still much about the humanity behind a piece of data. We have to remember there is always a human behind every data set and data point.

AIMed: What does winning the Abstract Competition mean to you?

Chen: I think winning the Abstract Competition validates me and my work. It proved to me that I can do something more rather than seeing the idea as a mere research project. I participate in the Mentor Assistance Program as a way to get some research experiences and a head start for college. When I first entered the Abstract Competition, I really didn’t expect anything. But now, it became a wonderful experience, I feel there is potential to what I am doing and if I keep pushing it forward, my research partners and I may actually be able to make a difference in the medical field.

AIMed: With that, how do you intend to bring your idea further?

Chen: At the moment, I will keep working on it at the University of California, San Diego Computer Center with my professor and research partners. We are now predicting new inhibitors and treatment options based on the old ones. We hope to highlight and give weights to old compounds that are more efficient at treating diabetic cataract, so we can ascertain a higher efficiency value for new compounds. On top of which, we are also trying to narrow our list of predictions down, as we will like to bring it to clinical testing.

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Author Bio

Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.